Interpreto: Demystifying Transformers with Explainability

This article introduces Interpreto, a library designed to improve the explainability of Transformer models. The development of such libraries is crucial for building trust and understanding in AI, especially as transformer-based models become more prevalent.

• •Interpreto aims to provide insights into how transformer models make decisions.
• •The library likely offers various methods for visualizing and interpreting model behavior.
• •Increased explainability can facilitate debugging and improve model reliability.